Mathieu Besançon
Associate Researcher
Grenoble, Auvergne-Rhône-Alpes, France
Summary
🤩
Rockstar🎓
Top SchoolMathieu Besançon is an associate researcher at Inria with 11 years of experience at the intersection of mathematical optimization, scientific software engineering, and industrial processes. He holds advanced doctoral training in applied mathematics and computer science and has combined academic research (postdoc at Zuse Institute Berlin) with hands-on engineering in industry and startups. Mathieu is a prolific Julia contributor, improving core language libraries and major packages such as Distributions.jl, JuMP.jl and the Julia packaging/build ecosystem (Yggdrasil), reflecting deep expertise in probabilistic modeling, optimization and reproducible build automation. His background in process engineering and applied signal analysis (Siemens, ArcelorMittal, Equisense) gives him a practical edge in translating complex models into deployable solutions for energy and industrial systems. Colleagues describe him as curious, collaborative and detail-oriented, often tackling low-level compatibility and performance issues that make research software production-ready. He combines rigorous theory with production-aware coding—an unusual blend that consistently improves code quality and usability in high-impact open-source scientific projects.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Engineering (B.Eng.), Energy and Process Engineering, Bachelor of Engineering (B.Eng.), Energy and Process Engineering at Technische Universität Carolo-Wilhelmina zu BraunschweigExchange Program in Applied Science and Engineering, Mathematics and Industrial Engineering, Exchange Program in Applied Science and Engineering, Mathematics and Industrial Engineering at Université de Montréal - Ecole polytechnique de MontréalDoctor of Philosophy - PhD, Applied Mathematics, Doctor of Philosophy - PhD, Applied Mathematics at Polytechnique MontréalScientific Baccalauréat, Sciences, Major in physics, English section - With honours, Scientific Baccalauréat, Sciences, Major in physics, English section - With honours at Lycée Jean TalonMaster of Science (M.Sc.), Process and Industrial Engineering, Master of Science (M.Sc.), Process and Industrial Engineering at Université de Technologie de CompiègneDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Centrale Lille
English, German, French, Spanish
Github Skills (52)
algorithm10
optimization10
algorithms10
graph-algorithms10
programming-language10
data-science10
package-development10
plugin-development10
statistics10
mathematical10
templater10
template-engine10
c1110
distributions10
data-structure10
Programming languages (26)
Github contributions (5)
JuliaStats/Distributions.jl
Aug 2018 - Oct 2022
A Julia package for probability distributions and associated functions.
Role in this project:
Data Scientist
Data ScientistContributions:4 releases, 62 reviews, 162 commits in 4 years 2 months
Contributions summary:Mathieu made numerous contributions to the `distributions.jl` repository, a Julia package for probability distributions. Their work primarily focused on implementing and improving statistical and probabilistic functions, including adding and testing functions like `logpdf` and `pdf` for various distributions. The user also worked on fixing bugs and enhancing existing documentation, demonstrating a commitment to code quality and usability. The user's commits showcase their expertise in statistical modeling and probability theory, essential for developing and maintaining this statistical package.
juliastatisticsdata-scienceprobability-distributions
sbromberger/LightGraphs.jl
Jan 2018 - Aug 2021
An optimized graphs package for the Julia programming language
Role in this project:Back-end Developer & Algorithm Implementer
Back-end Developer & Algorithm ImplementerContributions:7 reviews, 20 commits, 27 PRs in 3 years 7 months
Contributions summary:Mathieu primarily focused on modifying and refactoring the core codebase of the LightGraphs.jl package. They removed flow algorithms, implemented an iterator interface, and addressed deprecations and interface updates. The user also contributed by introducing new graph algorithms and features related to graph coloring and deterministic random functions, showcasing their work on both algorithmic and structural aspects of the library.
juliaprogramming-languagegraphlightgraphsgraph-theory
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